Notes for presentation on Monday 24th July scheduled as
I'll try to present a new slant:
EVOLVED LEVELS IN OUR UNIVERSE
(DRAFT: Liable to change)
Conference details: ICCM Warwick University July 2017
School of Computer Science, University of Birmingham
This is part of the Meta-Morphogenesis (M-M) project
Including the theory of evolved construction kits
This paper is
Abbreviated link http://goo.gl/TRG6ZF
A PDF version may be added later.
A partial index of discussion notes is in
Abstract published for ICCM
The Turing-inspired Meta-morphogenesis project begun in 2011 was partly
motivated by deep gaps in our understanding of mathematical cognition and other
aspects of human and non-human intelligence and our inability to model them. The
project attempts to identify previously unnoticed evolutionary transitions in
biological information processing related to gaps in our current understanding
of cognition. Analysis of such transitions may also shed light on gaps in
current AI. This is very different from attempts to study human mathematical
cognition directly, e.g. via observation, experiment, neural imaging, etc.
Fashionable ideas about "embodied cognition", "enactivism", and "situated
cognition", focus on shallow products of evolution, ignoring pressures to evolve
increasingly disembodied forms of cognition to meet increasingly complex and
varied challenges produced by articulated physical forms, multiple sensory
capabilities, geographical and temporal spread of important information and
other resources, and "other-related meta-cognition" concerning mental states,
processes and capabilities of other individuals. Computers are normally thought
of as good at mathematics: they perform logical, arithmetical and statistical
calculations and manipulate formulas, at enormous speeds, but still lack
abilities in humans and other animals to perceive and understand geometrical and
topological possibilities and constraints that (a) are required for perception
and use of affordances, and (b) play roles in mathematical, and
proto-mathematical, discoveries made by ancient mathematicians, human toddlers
and other intelligent animals. Neurally inspired, statistics-based (e.g."deep
learning") models cannot explain recognition and understanding of mathematical
necessity or impossibility. A partial (neo-Kantian) analysis of types of evolved
biological information processing capability still missing from our models may
inspire new kinds of research helping to fill the gaps. Had Turing lived long
enough to develop his ideas on morphogenesis, he might have done this.
Archimedes; Euclid; Kant; geometry; topology; cognition;
evolution; development; abstraction; non-empirical; non-contingent;
ONE OF THE HARDEST PROBLEMS IN SCIENCE:
Understanding natural intelligence
Including squirrel intelligence, crow intelligence, elephant intelligence,
toddler intelligence, octopus intelligence, intelligence of ancient
mathematicians like Archimedes, ...
Current AI models/explanations don't even come close.
Neither (as far as I know) do psychology, neuroscience, philosophy, ...
A few examples:
Several kinds of gap in our knowledge, e.g.
(a) Forms of intelligence used by humans (young and old) and other animals
(including individual variations within species, and
(b) What mechanisms make those forms of intelligence possible
(including forms of representation and manipulation of information)
(c) How those forms of evolution evolved, and
(d) How they develop in individuals
(e.g. linguistic competences and topological
and geometrical reasoning competences in humans).
The M-M hypothesis
Perhaps understanding more about intermediate stages in
evolution of various kinds of natural intelligence
will draw attention to gaps in our ideas about modelling and replication
of natural competences.
intelligence of various known and conjectured intermediate life forms in
the more or less distant past -- sometimes inferred indirectly from likely
challenges faced by evolutionary ancestors.
Thinking in detail about new challenges and
opportunities produced by early evolutionary
developments may provide new ideas about
What Can We Learn From Conjectured Evolutionary Transitions?
An example of crow intelligence (Betty reported in 2002):
For more information about Betty see Oxford Ecology Laboratory
Online videos show that in order to get a bucket of food out
of a vertical tube, she made hooks out of straight pieces of
wire found nearby, in at least four different ways.
What new forms of intelligence were required by the transition from
water-based to land-based-life, or from one kind of terrain to another, or when
a new type of predator or prey turned up, or when articulated body parts became
independently controllable, or when remote-sensing mechanisms evolved, or when
various kinds of flight developed, or when offspring were born or hatched
unable to feed, or to move, themselves, or when mating required cooperation?
possibility impossibility necessity
Problem: educational gaps in our culture
Part of the problem is that some of the hardest questions are not widely
understood by researchers, because formulating the questions accurately requires
concepts from epistemology, and metaphysics
which hardly anyone learns at school, nowadays.
E.g. the distinction between empirical and non-empirical knowledge, and the
closely related, but different, distinction between contingent and
non-contingent (necessary) truths and falsehoods, both
discussed by Immanuel Kant in 1781.
Necessity, impossibility, and related concepts have nothing to do with
statistical evidence or probabilities.
Those concepts are often assumed to be based on "possible-world semantics" (e.g.
what is true in this world and in all possible alternative worlds).
But for a child or non-human animal, or someone making a topological discovery,
impossibility has nothing to do with alternative complete
Only possible alternatives to a localised portion of this world are relevant.
A more detailed, but still incomplete, analysis was presented in my 1962 DPhil
Thesis, defending Kant.
"If a problem is too hard to solve,
try to find a related harder one"
(I can't now recall where I learnt that.)
Where do various forms of intelligence fit in the scheme of things?
LEVELS OF STRUCTURE IN OUR PART OF THE UNIVERSE
If we look beyond our planet we find far more structures of various kinds on
various scales: with new discoveries being added constantly.
Those are structures found by physicists/cosmologists
Max Tegmark's book:
Our mathematical universe, my quest for the ultimate nature of reality
What features make physical stuff able to implement and bring into existence
implementations of minds and their properties?
However all the above summarised structures on our planet must somehow have been
produced by the structures studied by physicists.
So any adequate fundamental physical theory needs to be capable of playing a
deep role in explanations of the origins and workings of all the structures on
our planet (and perhaps other more complex structures in other parts of the
universe, unknown to us).
But one of the things we have learnt from developments in computer science and
engineering in the last 70 years or so is that there are different sorts of deep
roles that a single powerful explanatory mechanism can have.
For example there is now a huge variety of uses of computers, differing
enormously in physical scale, in type of function, in kinds of applications, in
functions served: and all of these depend on a common substratum that can take
different but mathematically equivalent forms, including large arrays of
bistable switches that can be made to change their on/off patterns under the
control of other switches.
WADDINGTON'S EPIGENETIC LANDSCAPE
AN ALTERNATIVE VIEW OF EPIGENESIS
Figure adapted from:
Jackie Chappell and Aaron Sloman, 2007,
"Natural and artificial meta-configured altricial
International Journal of Unconventional Computing, 3, 3, pp. 211--239,
Can we extend some those ideas about epigenesis in organisms
to epigenesis in the universe as a whole?
For now let's consider this only in relation to evolution on one planet,
using ideas developed in the Meta-Morphogenesis project
especially the work on fundamental and derived construction kits used by natural
(still extending ideas published in
A sketch of epigenesis on a universal scale (a)
A sketch of epigenesis on a universal scale (b)
TO BE COMPLETED
REFERENCES AND LINKS
Critique of Pure Reason
Aaron Sloman, 2013,
Virtual Machinery and Evolution of Mind (Part 3):
Meta-Morphogenesis: Evolution of Information-Processing Machinery, in
Alan Turing - His Work and Impact,
Eds. S. B. Cooper and J. van Leeuwen,
Elsevier, Amsterdam, pp. 849-856,
Aaron Sloman, 2017,
Construction Kits for Biological Evolution, in
The Incomputable: Journeys Beyond the Turing Barrier,
Eds. S. Barry Cooper and Mariya I. Soskova,
Ideas still being developed at:
Installed: 4 Jul 2017
Last updated: 10 Jul 2017; 16 Jul 2017
School of Computer Science
The University of Birmingham